AI ethics and bias Deep-Dive Analysis
Abstract This report conducts a comprehensive deep-search synthesis of three sources addressing AI ethics and bias. Facing uneven data, opaque models, and governance gaps, the literature collectively emphasizes that bias emerges from data, algorithmic design, and organizational processes, with significant implications for fairness, privacy, and trust. When one source (Source 1) is inaccessible for full … Read more